DATA SCIENTIST
JOBS IN
NEW ZEALAND
Data scientists – driving our future
Demand for data scientists with the right skills, curiosity and talent to create and manage complex data models has skyrocketed. When used effectively, data can transform businesses, improve decision making, accelerate innovation, improve the customer experience and drive operational efficiency.
But it needs the right people to make this happen. Experts who can convert raw unstructured data and who can turn Big Data into meaningful insights, fast, are in demand. Let us help you to discover the opportunities.
Find my next Data Scientist job in New Zealand
Almost all organisations are looking at how they can better use data to power their growth. But you’ll need our support to find the right one for you. If you’re a data scientist with the skills to match your ambitions, we’ll give you access to the data science roles nobody else has from a complete range of employers.
Work with us and you’ll get an expert, lifelong career partner who will help assess your options, listen to your feedback and who will secure your next role quickly – being in demand provides you with the opportunities, we can help you to capitalise on them.
Find your nearest office to get in touch with us, send us your CV or browse our latest available Data Scientist jobs.
Latest Data Science jobs
Data Modeller
Wellington |
|
HR Reporting & Insights Analyst
Wellington Up to 110k |
Your Data Scientist job questions, answered
-
Collect, gather, analyse, and then visualise information to create insights that will drive business solutions
-
Source additional information through the creation of new data and utilisation of any and all relevant statistical techniques, software packages, program languages and data infrastructure to resolve specific business issues
-
Use predictive modelling to optimise business goals and outcomes
-
Collaborate with other departments to develop and implement custom data models and algorithms
-
Extract insights from data and communicate these effectively using appropriate technologies to stakeholders and other relevant parties
-
Streamline and automate processes using artificial intelligence and machine learning
Mathematics is a significant component in any data science job as concepts within mathematics are critical in identifying patterns and creating algorithms. Calculus, linear algebra, and statistics are three topics that are regularly used in Data Scientist jobs. It is important to understand principles of calculus and how they might impact your modelling.
Candidates who possess a genuine strength in probabilities and statistics will be in an advantageous position. Calculating the likelihood of an event is an intuitive concept that Data Scientists use daily when employing methods such as scenario analysis. In relation to statistics, you should be familiar with tree-based methods and competent in the application of validation techniques.
Business acumen relates to the knowledge and understanding of a particular field. Every industry has its own intricacies, and this should be recognised as an opportunity for you to gain a deep understanding of a particular field in order to stand out. Learning industry intricacies is a gradual process that will be made easier if you can display strength in other fundamental areas such as computer science and mathematics.
The value of communication as a Data Science skill should not be underestimated. These skills are important during the discovery and goal phase but are more prevalent in the presentation of results. Data Scientists are typically required to communicate their results to key stakeholders, including executives. The ability to deliver results in a manner that is easy to understand, yet insightful and compelling, is where the value of a Data Scientist is exhibited. Employers are looking for Data Scientists who can tell them how the analysed data will impact their business.
Data Science is an expanding field that is constantly evolving to meet technological advances and changing demands. The general route to a Data Scientist is to progress from a BI Analyst or Data Analyst Role with academic understanding of Data Science concepts. Applicants with a background in computer science or mathematics can explore entry-level data analytics, business intelligence and data science jobs before progressing to a senior Data Scientist position.
- Finance - Data Scientists are in genuine demand in financial sectors such as banking, trading, and insurance. Employers are utilising data science to manage customer data, automate risk management, detect fraud, conduct algorithmic trading and real-time analysis.
- Healthcare - Imaging is a key area as computers can learn to interpret images such as MRI’s and X-rays. They can also identify patterns in data and detect tumours.
- Marketing - Big data in marketing provides an opportunity to better understand the target audience. Data science can be applied to areas relating to customer engagement, retention, dynamic pricing, profiling, and search engine optimisation.
- Programming Languages - Python, R and SQL
- Machine Learning & Artificial Intelligence – BigML and Apache (Spark, Hadoop etc)
- Mathematics/Statistics - SAS and MATLAB
- Data Visualisation - Tableau, D3.js, Qlikview, Matplotlib, Microsoft BI